Gerontology at IgMin Research | Medicine Group
We strive to foster an ecosystem where different fields of study can collaborate for progress.
About
Gerontology is the scientific study of aging, focusing on the physical, psychological, and social changes that occur as individuals grow older. This field encompasses research into the biological processes of aging, age-related diseases, and the challenges associated with an aging population. Researchers in Gerontology seek to improve the quality of life for older adults by exploring strategies for healthy aging, disease prevention, and comprehensive care models that address the unique needs of the elderly.
The study of Gerontology integrates insights from biology, medicine, sociology, and psychology to address the multifaceted aspects of aging. By investigating areas such as cognitive health, mobility, and social support systems, this field aims to promote well-being and independence among older adults. Advancements in Gerontology are essential for shaping policies, healthcare practices, and interventions that enhance longevity and improve the overall health outcomes of aging populations.
Why publish with us?
Global Visibility – Indexed in major databases
Fast Peer Review – Decision within 14–21 days
Open Access – Maximize readership and citation
Multidisciplinary Scope – Biology, Medicine and Engineering
Editorial Board Excellence – Global experts involved
University Library Indexing – Via OCLC
Permanent Archiving – CrossRef DOI
APC – Affordable APCs with discounts
Citation – High Citation Potential
Which articles are now trending?
Research Articles
- Wishful Thinking or Valuable Forecasts? The Value of Policy Rate Predictions in Sweden
- Challenge and Readiness to Implemented Geothermal Energy in Indonesia
- A Model of the Enforcement of Laws in Tramadol Drug Abusers
- Sensor-based Sorting using De-XRT Sensor Applied to a Greenfield Copper Ore Project in Southern Brazil
- Federated Learning- Hope and Scope
- Enhancing Material Property Predictions through Optimized KNN Imputation and Deep Neural Network Modeling
